1 Information-efficient human-computer interfaces David MacKay Department of Physics, University of Cambridge - with David Ward and Alan Blackwell

2 Information-efficient text entry David MacKay Department of Physics University of Cambridge - with David Ward and Alan Blackwell

3 Hands-free writing Information-efficient human-computer interfaces David MacKay Department of Physics - with David Ward and Alan Blackwell

4 Dasher – A Data Entry Device Using Continuous Gestures and Language Models David Ward, Alan Blackwell, and David MacKay University of Cambridge Original concept: MacKay and Lewicki, 1997

5 A famously inefficient writing method Alternative keyboard layouts

6 Text entry for handheld devices Miniature or rearranged keyboards Gestural alphabets Unistrokes

7 Dynamic selection Word-completion Write ambiguously, disambiguate later  T9  Spellchecker  Shorthand dsmbgu8 l8r Quikwriting

8 What’s wrong with keyboards?

9 1. Information content of English  1 bit per character. Each keypress on a QWERTY keyboard could convey ~ 6 bits. 2.Keyboard – digital : hands - analog. A pointing finger can generate information at a rate of 14 bits per second (Drury and Hoffmann). So... Potential writing speed of just one finger is 14 characters per second? (  170 words per minute) Why keyboards are inefficient

10 Writing and text-compression Text compression Text Bit string (preferably short) Gesture (preferably brief) Text Writing

11 Writing and text-compression Optimal text compression – Arithmetic coding Text Bit string, viewed as a real number Text Real gesture Writing with Dasher probabilistic model

12 Demonstration - available for GNU/linux, windoze, and pocket PC

13 Arithmetic Coding a c P(x 1 =a) P(x 1 =c) P(x 1 =b) a b c P(x 1,x 2 )=P(x 1 )P(x 2 |x 1 ) P(x 1,x 2,x 3 )=P(x 1 )P(x 2 |x 1 )P(x 3 |x 1,x 2 ) P(x 1 =a,x 2 =a) P(x 1 =a,x 2 =c) String S=x 1 x 2 x 3... Divide the interval (0,1] into intervals equal to the probabilities of the symbols. 0 1

14 Dynamics Point to where you want to go  Like driving a car  Motion sickness? Passengers may get sick, driver doesn’t

15 Benefits Keyboard – usually one gesture per character Dasher – some gestures select more than one character Inaccurate gestures can be compensated for by later gestures

16 Benefits continued Mode-free. Can be used with any alphabet (e.g. Hiragana!) Requires no special learning. (knowledge of the chosen alphabetical order is helpful) Can add extra characters to alphabet without any extra learning.

17 The Language Model Based on PPM (Prediction by Partial Match), a context-based model. Compresses most English to about 2 bits per character (could be improved) Fast Adaptive Works with any language

18 Evaluation 10 volunteers Dictation task Emma, by Jane Austen Automated dictation system with recorded speech 12 Dasher exercises, each 5 minutes long Keyboard exercises between Dasher sessions Measured writing speed and word error rate Dasher Keyboard 5 min3 min

19 Results - writing speeds Writing speed (cpm) Exercise number Writing speed (cpm) Exercise number DasherKeyboard 50 wpm 25 wpm

20 Results – information rate

21 Results – writing errors Percentage of words wrong Exercise number Percentage of words wrong DasherKeyboard

22 Comparison with other devices Dasher Bellman OPTI Half-QWERTY ABC-tapping Hand printing QWERTY-tapping TCK2 Chorded, one hand one hand keyboard stylus on large tablet Stylus fluctuating keyboard

23 Mobile Text Entry Pocket PC Driven by stylus & touchscreen

24 Palmtop Results

25 The main defect of Dasher It demands visual attention (like any predictive system)

26 Eye gaze tracking

27 Hands-free writing

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29 Eyetracking results

30 Eyetracking results

31 Another hands-free solution Head-mouse

32 Different Character Sets Include capital letters, punctuation Japanese – Hiragana

33 Exploits redundancy of language Rapid learning rate Applications - Mobile text entry - Special needs Download Dasher! - available for linux, windoze, and iPaq handheld Summary of Dasher

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35 Download Dasher - available for linux, windoze, and pocket PC Development of Dasher is supported by the Gatsby Charitable Foundation

36 Some Uses for Probabilities “Bayesian Methods for Adaptive Models” Fast approximate inference Error-correcting codes Efficient data-entry devices